Nature.com
DeepMind’s AlphaFold tool has determined the structures of around 200 million proteins.
From today, determining the 3D shape of almost any protein known to science will be as simple as typing in a Google search. Researchers have used AlphaFold — the revolutionary artificial-intelligence (AI) network — to predict the structures of some 200 million proteins from 1 million species, covering nearly every known protein on the planet. The data dump will be freely available on a database set up by DeepMind, Google’s London-based AI company that developed AlphaFold, and the European Molecular Biology Laboratory’s European Bioinformatics Institute (EMBL-EBI), an intergovernmental organization near Cambridge, UK. “Essentially you can think of it covering the entire protein universe,” DeepMind CEO Demis Hassabis, said at a press briefing. “We’re at the beginning of new era of digital biology.” The 3D shape, or structure, of a protein is what determines its function in cells. Most drugs are designed using structural information, and accurate maps are often the first step to discoveries about how proteins work. DeepMind developed the AlphaFold network using an AI technique called deep learning, and the AlphaFold database was launched one year ago with 350,000 structure predictions covering nearly every protein made by humans, mice and 19 other widely studied organisms. The catalogue has since swelled to around 1 million entries. “We’re bracing ourselves for the release of this huge trove,” says Christine Orengo, a computational biologist at University College London, who has used the AlphaFold database to identify new families of proteins. “Having all the data predicted for us is just fantastic.”
